Performance evaluation with portfolio holdings information

This paper surveys recent academic research that uses portfolio holdings to evaluate the performance of an asset manager. These approaches mitigate the benchmark-choice problem of Roll (1978), as well as providing a much more precise attribution of the sources of manager returns. Although originally developed with U.S. data, recent papers have applied these approaches to European, Asian, and Australian equity managers. All surveyed approaches can be integrated into the Brinson, Hood, and Beebower (1986) attribution method, if we allow the composition of the benchmark portfolio to evolve through time according to the observed portfolio holdings of an asset manager.     

Portfolio optimization for an investor with a benchmark

The most common equity mandate in the financial industry is to try to outperform an externally given benchmark with known weights. The standard quantitative approach to do this is to optimize the portfolio over short time horizons consecutively, using one-period models. However, it is not clear that this approach actually yields good performance in the long run. We provide a theoretical justification to this methodology by verifying that applying the one-period benchmark-relative mean-variance portfolio, i.e., the industry standard optimal portfolio, continuously is in fact the solution to a specific continuous time portfolio optimization problem: a maximum expected utility problem for an investor who is compared against a benchmark and evaluates her performance based on exponential utility at a deterministic future date.     

内部收益保证下养老基金的最优资产配置

研究内部收益保证下DC型养老基金的最优资产配置问题。利用鞅方法，在HJM利率期限结构下求得了最优资产配置的显性解。结论表明最优投资策略分为四部分：投机策略、利率套期保值策略、基准组合的复制策略及一揽予债券卖空策略。最后对最优策略的动态行为进行了数值分析。     

The long-run performance of initial public offerings: Stochastic dominance criteria

We examine the long-run performance of initial public offerings (IPOs) using the idea of stochastic dominance. The analysis is a first attempt using a non-event study methodology to evaluate long-horizon performance. We find that there is no first-order stochastic dominance relation between the IPO portfolio and the benchmark of a broad index or a portfolio including either small size or low book-to-market stocks. However, those benchmarks second-order stochastically dominate the IPO portfolio. When using a portfolio including both small size and low book-to-market stocks as benchmark, there is a clear dominance of the IPO portfolio over the benchmark for both orders. Our findings generally imply that the question of assessing portfolio performance between IPO firms and benchmark portfolios depends critically on the specific construction or the cumulative distribution function of the benchmark portfolios. The empirical results also potentially explain the extent of sample dependent results in the literature.     

Retaining and satisfying project managers – antecedents and outcomes of project managers’ perceived organizational support

Although theory and research from the domains of organizational behavior and human resource management suggest that individuals’ perceived organizational support (POS) plays a crucial role in enhancing job satisfaction and in reducing turnover intentions, there is a lack of research applying Organizational Support Theory to the realm of project management. Project-based organizations have an increasing demand for highly qualified project managers who feel supported by their employing organization and intend to remain in their positions. Therefore, the primary objective of the present study was to investigate predictors of project managers’ POS (both from a career management and from a project portfolio management perspective) and to examine how this variable related to their job satisfaction and intention to quit their project manager position. Using a sample of 541 project managers and 135 project portfolio coordinators nested in 135 firms, the analysis revealed that POS related positively to project managers’ job satisfaction and negatively to their turnover intention. A career path for project managers was positively associated with POS, especially when it was accompanied by adequate qualification opportunities. Results further stress the significance of top management involvement and the support of project management offices for project managers’ POS.     

Do investors still benefit from international diversification with investment constraints?

This paper empirically investigates the potential benefits of international diversification for the U.S. investor with various investment constraints from both long-term and time-rolling perspectives. While the addition of portfolio bounds makes asset allocation more feasible, our findings suggest that adding short-selling and over-weighting constraints reduce but do not completely eliminate the diversification benefits of international investment. The over-time analyses show that diversifying portfolios internationally is still beneficial even though financial markets are becoming more integrated. The out-of-sample test suggests that the Markowitz model does not necessarily realize improved mean–variance efficiency but demonstrates risk reduction. The significant time variation in optimal asset allocation implies the necessity for the fund manager to rebalance international portfolio dynamically.     

Portfolio optimization based on GARCH-EVT-Copula forecasting models

This study uses GARCH-EVT-copula and ARMA-GARCH-EVT-copula models to perform out-of-sample forecasts and simulate one-day-ahead returns for ten stock indexes. We construct optimal portfolios based on the global minimum variance (GMV), minimum conditional value-at-risk (Min-CVaR) and certainty equivalence tangency (CET) criteria, and model the dependence structure between stock market returns by employing elliptical (Student-$t$ and Gaussian) and Archimedean (Clayton, Frank and Gumbel) copulas. We analyze the performances of 288 risk modeling portfolio strategies using out-of-sample back-testing. Our main finding is that the CET portfolio, based on ARMA-GARCH-EVT-copula forecasts, outperforms the benchmark portfolio based on historical returns. The regression analyses show that GARCH-EVT forecasting models, which use Gaussian or Student-$t$ copulas, are best at reducing the portfolio risk.     

Dynamic portfolio choice under ambiguity and regime switching mean returns

I examine a continuous-time intertemporal consumption and portfolio choice problem under ambiguity, where expected returns of a risky asset follow a hidden Markov chain. Investors with Chen and Epstein's (2002) recursive multiple priors utility possess a set of priors for unobservable investment opportunities. The optimal consumption and portfolio policies are explicitly characterized in terms of the Malliavin derivatives and stochastic integrals. When the model is calibrated to U.S. stock market data, I find that continuous Bayesian revisions under incomplete information generate ambiguity-driven hedging demands that mitigate intertemporal hedging demands. In addition, ambiguity aversion magnifies the importance of hedging demands in the optimal portfolio policies. Out-of-sample experiments demonstrate the economic importance of accounting for ambiguity.     

A coupled Markov chain approach to credit risk modeling

We propose a Markov chain model for credit rating changes. We do not use any distributional assumptions on the asset values of the rated companies but directly model the rating transitions process. The parameters of the model are estimated by a maximum likelihood approach using historical rating transitions and heuristic global optimization techniques.We benchmark the model against a GLMM model in the context of bond portfolio risk management. The proposed model yields stronger dependencies and higher risks than the GLMM model. As a result, the risk optimal portfolios are more conservative than the decisions resulting from the benchmark model.     

On portfolio optimization: How and when do we benefit from high‐frequency data?

We examine how the use of high‐frequency data impacts the portfolio optimization decision. Prior research has documented that an estimate of realized volatility is more precise when based upon intraday returns rather than daily returns. Using the framework of a professional investment manager who wishes to track the S&P 500 with the 30 Dow Jones Industrial Average stocks, we find that the benefits of using high‐frequency data depend upon the rebalancing frequency and estimation horizon. If the portfolio is rebalanced monthly and the manager has access to at least the previous 12 months of data, daily data have the potential to perform as well as high‐frequency data. However, substantial improvements in the portfolio optimization decision from high‐frequency data are realized if the manager rebalances daily or has less than a 6‐month estimation window. These findings are robust to transaction costs. Copyright © 2009 John Wiley & Sons, Ltd.     

The Cost Effectiveness of the UK's Sovereign Debt Portfolio*

This paper provides a recursive empirical analysis of the scope for cost minimization in public debt management when the debt manager faces a given short‐term interest rate dictated by monetary policy as well as risk and market impact constraints. It simulates the ‘real‐time’ interest costs of alternative portfolios for UK government debt between April 1985 and March 2000. These portfolios are constructed using forecasts of return spreads based on a recursive modelling procedure. While we find statistically significant evidence of predictability, the interest cost savings are quite small when portfolio shares are constrained to lie within historical bounds.     

Implied Sharpe ratios of portfolios with options: Application to Nikkei futures and listed options

We propose a criterion for portfolio selection, implied excess Sharpe ratio. The implied excess Sharpe ratio is intended as an excess Sharpe ratio (versus the underlying stock) that investors can expect to enjoy from portfolios that include options and is a useful ex ante indicator that can be easily calculated. There are a variety of ways to include options in a portfolio, but we theoretically show that the combination that produces the largest implied excess Sharpe ratio is the best way to maximize the short-term Sharpe ratio. The selection process uses implied excess Sharpe ratio, which is easily calculated from stock lending fees implied by stock prices and actual stock lending fee. It does not require historical simulation or prediction of share price average growth rates and is highly transparent as it can be easily reproduced (at a low calculation cost). Hence, the implied excess Sharpe ratio is a simple but effective tool for investors seeking returns in exchange for a certain amount of risk that want to use the options market efficiently. The short-term Sharpe ratio is not necessarily the only criterion, but is a rational benchmark of portfolio performance closely related to criteria such as the long-term Sharpe ratio and maximum drawdown. To examine the benefit of the concept, we construct an investment strategy that automatically selects from multiple candidate portfolios that are made up of combinations of Nikkei futures and Nikkei listed options the portfolio with the largest implied excess Sharpe ratio. Back-testing shows that this investment strategy performs well over the long term as well.     

一种基于相对风险的风险预算方法

风险预算是针对积极投资管理者进行的,所以我们预算和控制的风险主要来自于相对风险而不是绝对风险。本文中的风险预算方法则是在相对风险的基础上,利用边际跟踪误差、相对于基准的调整量、积极因子和积极beta系数等一系列相对概念。通过两个最优化模型,分别在战略资产配置和战术资产配置过程中,将风险配置于投资管理者和管理者资产,并且根据投资者,给定的管理者风险贡献和管理者实际风险贡献之间的误差,进行及时的动态调整,从而完成风险预算的整个过程。     

Robustness of stable volatility strategies

The paper analyzes the robustness of stable volatility strategies, i.e. strategies in which the portfolio weight of the stock is inversely proportional to its local volatility. These strategies are optimal for a CRRA investor if the stock follows a diffusion process, the expected excess return is proportional to its volatility, and the hedging demand is zero. We assess the performance of stable volatility strategies when these restrictive assumptions do not hold, in particular, when the risk premium is not proportional to volatility and when the stock price is subject to jumps. We find that stable volatility strategies are indeed robust or close to robust under a maxmin decision rule. In addition to our theoretical results, we perform a simulation analysis to evaluate strategies that scale the portfolio weight by the volatility, variance or a constant portfolio weight, and also analyze the strategies using empirical excess returns. Both analyses confirm the robustness of stable volatility strategies.     

IPO and Aftermarket Performance of Single‐Listed Chinese ADRs

This paper analyzes the post‐IPO and long‐run aftermarket performances of single‐listed Chinese ADRs during the 2004–2010 period. Single‐listed ADRs are traded daily in major exchanges in the United States, but their underlying shares are not traded in the issuer's home market. Our results show that over the short‐run, buy‐and‐hold abnormal returns of single‐listed Chinese ADRs following their IPO are not significantly different from the typical post‐IPO performance of stocks in U.S. exchanges, including that of traditional dual‐listed Chinese ADRs. Nevertheless, over the longer horizon, the excess returns of a portfolio composed solely of single‐listed Chinese ADRs outperform a portfolio of dual‐listed Chinese ADRs, but underperform a benchmark portfolio composed of U.S. firms matched on the basis of their IPO date. We also find that the portfolio formed solely of single‐listed Chinese ADRs exhibits significantly distinct loadings on the common portfolio factors from the portfolio formed of dual‐listed Chinese ADRs and from the benchmark portfolio of U.S. stocks.     

Mutual fund flows and window-dressing

We use a sequential game to analyze an agency problem in the mutual fund industry where a representative fund manager considers window-dressing his portfolio holdings for the purpose of attracting fund flows from a representative investor. The manager is motivated to window-dress to improve the investor's perception of managerial skill which may positively affect fund flows in the next period. However, the investor may suspect window-dressing and thus downgrade perceived managerial skill. The model supports a Bayesian Nash equilibrium where the manager window-dresses only when receiving a low return in the first period and the investor withdraws funds only when observing low returns in both periods. Consequently, we show that window-dressing is a rational behavior even when fund outflows may result.     

Performance measurement and best-practice benchmarking of mutual funds: combining stochastic dominance criteria with data envelopment analysis

We propose a method for mutual fund performance measurement and best-practice benchmarking, which endogenously identifies a dominating benchmark portfolio for each evaluated mutual fund. Dominating benchmarks provide information about efficiency improvement potential as well as portfolio strategies for achieving them. Portfolio diversification possibilities are accounts for by using Data Envelopment Analysis (DEA). Portfolio risk is accounted for in terms of the full return distribution by utilizing Stochastic Dominance (SD) criteria. The approach is illustrated by an application to US based environmentally responsible mutual funds.     

Selecting a discrete portfolio

We study the problem of selecting an optimal portfolio out of a finite set of available assets. Assets are characterized by their expected returns and the covariance matrix, and investors are assumed to have a mean–variance utility, that is, their utility function is linear in the mean and variance of the portfolio they hold.When assets are negatively correlated, or even when a slightly more general condition is satisfied, we provide an algorithm for selecting an optimal portfolio. We illustrate the usefulness of this algorithm by some comparative statics result. When assets can be positively correlated, we deliver a negative result regarding the existence of useful algorithms for selecting an optimal portfolio.     

Optimal dividend strategies with time-inconsistent preferences

This paper studies the optimal dividend strategies of an insurance company when the manager has time-inconsistent preferences. We consider the problem for a naive manager and a sophisticated manager, and analytically derive the optimal dividend strategies when claim sizes follow an exponential distribution. Our results show that the manager with time-inconsistent preferences tends to pay out dividends earlier than her time-consistent counterpart and that the sophisticated manager is more inclined to pay out dividends than the naive manager. Furthermore, we extend these results to the case with claim sizes following a mixed exponential distribution, and provide a numerical analysis to reveal the sensitivity of the optimal dividend strategies to changes in the premium, claims and surplus volatility.     

Interest rates and financial fragility

How do the interest rates banks earn on their assets affect the susceptibility of the banking system to a self-fulfilling run by depositors? I study this question in a version of the model of Diamond and Dybvig (1983) with limited commitment and a non-trivial portfolio choice. I show that the relationship between these interest rates and financial fragility is often non-monotone. For example, a small increase in the return on illiquid investment (or a small increase in the term premium) may raise banks’ susceptibility to a run, while a larger increase would make the banking system more stable. The same is true for changes in short-term rates, holding the longer-term rates fixed. I provide a precise characterization of these comparative statics of financial fragility.